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<table width="100%" summary="page for daphnids"><tr><td>daphnids</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Daphnia test</h2>

<h3>Description</h3>

<p>The number of immobile daphnids &ndash;in contrast to mobile daphnids&ndash; out of a total of 20 daphnids was counted 
for several concentrations of a toxic substance.
</p>


<h3>Usage</h3>

<pre>data(daphnids)</pre>


<h3>Format</h3>

<p>A data frame with 16 observations on the following 4 variables.
</p>

<dl>
<dt><code>dose</code></dt><dd><p>a numeric vector</p>
</dd>
<dt><code>no</code></dt><dd><p>a numeric vector</p>
</dd>
<dt><code>total</code></dt><dd><p>a numeric vector</p>
</dd>
<dt><code>time</code></dt><dd><p>a factor with levels <code>24h</code> <code>48h</code></p>
</dd>
</dl>



<h3>Details</h3>

<p>The same daphnids were counted at 24h and later again at 48h.
</p>


<h3>Source</h3>

<p>Nina Cedergreen, Faculty of Life Sciences, University of Copenhagen, Denmark.
</p>


<h3>Examples</h3>

<pre>

## Fitting a model with different parameters
## for different curves
daphnids.m1 &lt;- drm(no/total~dose, time, weights = total, 
data = daphnids, fct = LL.2(), type = "binomial")

## Goodness-of-fit test
modelFit(daphnids.m1)

## Summary of the data
summary(daphnids.m1)

## Fitting a model with a common intercept parameter
daphnids.m2 &lt;- drm(no/total~dose, time, weights = total, 
data = daphnids, fct = LL.2(), type = "binomial", 
pmodels = list(~1, ~time))

</pre>


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